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CF azure-architecture

Expert guidance for designing Azure solutions using Azure Architecture. Covers reference architectures, solution ideas, design patterns, technology choices, architecture styles, best practices, anti-patterns, example workloads, and migration guides. Use when designing Azure AI/RAG, AKS microservices, data/analytics, IoT, or SAP/mainframe migration solutions, and other Azure Architecture related development tasks.

MicrosoftDocs/Agent-Skills Agent Skills author: MicrosoftDocs CC-BY-4.0 1 file body ≈ 14 672 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Expert guidance for designing Azure solutions using Azure Architecture.

As a process F 29/100 · No process to follow — References files that are not bundled: security.md

ReferenceAzureKubernetesAWSInfrastructuretype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
85/100
safety, quality, tests
Safety 60%
99
Quality 40%
65
Run on models
none yet
Process rating
F
29/100
No process to follow
References files that are not bundled: security.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • low Risky intent intent-offensive-security SKILL.md:383
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    | Implement ransomware-resilient backups with Azure Backup | https://learn.microsoft.com/en-us/azure/architecture/security/ransomware-resilient-backup-architecture/ |

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 14672 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: security.md
  • note edit-residue the text marks something as outdated (lines 169, 307): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 29/100

Will not run. References files that are not bundled: security.md
  • 0Tools and files. 1 referenced file(s) missing: security.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Execution cost. Instruction body is 14672 tokens: crowds the task out of the window
  • 50Steps. 2 steps
  • 50Failures and branches. 0 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 416: enough signal without eating the budget
  • +4Structure: 12 headings
  • +4Has examples (0 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.